Garuda - Garba Rujukan Digital

Perancangan Situs Administrasi Pendaftaran Anggota dan Kegiatan dengan Metode Jaringan Unicast Wirawan, Cipto; Darmanto, Tony; Willay, Thommy
Jurnal Esensi Infokom : Jurnal Esensi Sistem Informasi dan Sistem Komputer Vol 9 No 1 (2025)
Publisher : Institut Bisnis Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55886/infokom.v9i1.959

Penggunaan teknologi berbasis web dan arsitektur microservices sebagai sarana komunikasi data telah menjadi kebutuhan yang sangat krusial dalam pengembangan sistem informasi modern. Dengan memanfaatkan perkembangan teknologi ini, organisasi dapat mengolah dan mengirimkan data secara efisien dan terintegrasi. Penelitian ini bertujuan untuk menghasilkan suatu sistem informasi yang mampu menyampaikan data registrasi serta pembayaran keanggotaan secara cepat, tepat dan terstruktur dengan metode unicast untuk menunjang kebutuhan operasional Lions Clubs Multiple District 307 (LC MD 307) dalam pengelolaan data anggota serta pembayaran iuran keanggotaan. Berdasarkan penelitian yang telah dilakukan, dapat disimpulkan bahwa data keanggotaan yang dikirimkan baik dari modul registrasi menuju modul pembayaran maupun sebaliknya dapat diterima dan diproses dengan baik menggunakan Apache Kafka sebagai message broker, yang memungkinkan komunikasi komunikasi antar modul yang handal dengan prinsip metode publish-subscribe. Sistem dibangun menggunakan Framework Laravel dengan arsitektur microservices yang memungkinkan manajemen data anggota secara digital dan terintegrasi, otomatisasi verifikasi pembayaran iuran keanggotaan, registrasi peserta kegiatan, serta pelaporan dalam operasional organisasi seperti: data keanggotaan, daftar registrasi serta kehadiran peserta kegiatan secara lebih akurat.

Implementation of Prototyping and System Usability Scale In The Point of Sales Information System at CV Kharisma Lestari Antonius, Antonius; Darmanto, Tony; Willay, Thommy
International Journal of Multidisciplinary Sciences and Arts Vol. 4 No. 4 (2025): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v4i4.7356

CV Kharisma Lestari is a retail business that faces obstacles in its sales and inventory management systems due to its continued use of manual processes. This study aims to develop a Point of Sales (POS) Information System by applying the prototyping method to improve the operational efficiency of CV Kharisma Lestari. The prototyping method was chosen for its ability to actively involve users from the early stages, so that the resulting system can meet their needs and expectations. This study uses a Research and Development (R&D) approach with prototyping stages : communication, quick plan, modeling quick design, construction of prototype, and deployment delivery and feedback. The results of the study show that the POS system developed successfully automates the sales transaction process, manages inventory data in real-time, and generates accurate inventory and sales reports. The implementation of this system has a significant impact on reducing transaction time by up to 70% and increasing inventory data accuracy. The System Usability Scale (SUS) test on the system resulted in a score of 85.8, which indicates a very high level of user acceptance (usability). Thus, the prototyping method has proven to be effective in producing an information system that is not only functional but also easy to use, as it is able to capture user needs and feedback.

Rancang Bangun Sistem Informasi Administrasi Pada Dadung Gym Hendra Wijaya; Tony Darmanto; Sandi Tendean
INTEKSIS Vol 12 No 2 (2025): November 2025
Publisher : LPPM Universitas Widya Dharma Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66003/inteksis.v12i2.10589

The rapid development of fitness centers has prompted the need for efficient administrative systems. Dadung Gym in Pontianak faces challenges in managing member data and transactions due to reliance on traditional administrative methods. This study aims to design a mobile-based information system to reduce data processing errors, enhance service quality, and support strategic decision-making. Using an object-oriented approach with UML modeling, the system is developed with Flutter for the application framework, Firebaseas the database, and Visual Studio Code as the development tool. The new system automates data recording and offers features such as membership management, GPS-based attendance, and integrated reporting. Implementation of this mobile-based system is expected to improve service quality, simplify administrative processes, and provide a foundation for future business development at Dadung Gym Pontianak.

Rancang Bangun Sistem Virtual Mouse Dengan Hand Gesture Recognition Menggunakan Convolutional Neural Network Jeffrey Ken; Tony Darmanto; Hendro
INTEKSIS Vol 12 No 2 (2025): November 2025
Publisher : LPPM Universitas Widya Dharma Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66003/inteksis.v12i2.10591

The development of human-computer interaction technology continues to grow, especially in the context of hand gesture recognition for device control applications. One interesting application is designing a virtual mouse system based on hand gesture recognition using a Convolutional Neural Network (CNN). This research was conducted to overcome the limitations of conventional input devices and utilize modern technology to create a more sophisticated and adaptive control system. This research focuses on developing a system that is able to identify and interpret hand gestures accurately in a real-time environment. The proposed system utilizes an RGB camera to capture images of the user's hand gestures, which are then processed by a CNN that has been pre-trained to recognize different gestures. Experiments were carried out using a gesture dataset that included variations in pose and hand orientation to evaluate the system's performance in recognizing gestures with a sufficient level of accuracy. The research results show that the system can successfully control the movement of the cursor on the computer screen with high accuracy, validating the potential practical application of this technology in improving the user experience in computer interactions. The implication of this research is a contribution to the development of more intuitive and effective user interfaces through the integration of hand gesture technology in virtual mouse applications.

Aplikasi Klasifikasi Penyakit Pada Tanaman Jambu Air Menggunakan Metode CNN Antonius Oktavian Jethro; Tony Darmanto; Riyadi J. Iskandar
INTEKSIS Vol 12 No 2 (2025): November 2025
Publisher : LPPM Universitas Widya Dharma Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66003/inteksis.v12i2.10592

Diseases in water apple plants can significantly reduce the quality and quantity of the harvest, thus an accurate early classification system is needed. This research aims to develop an automatic classification system to assist in the early diagnosis of diseases in water apple plants. This system uses a Convolutional Neural Network (CNN) model with the MobileNetV2 architecture optimized through fine-tuning techniques. The dataset was obtained from Kaggle, Roboflow, and direct data collection, with a distribution of 80 percent training data, 10 percent validation data, and 10 percent testing data. The model was trained to recognize nine different conditions from images of leaves and fruits, then integrated into a web application. Testing results showed very good performance, with a final accuracy of 94 percent and a balanced F1-Score of 93 percent on unseen test data. However, the model faces challenges in distinguishing diseases with high visual similarity, especially in the class of leaves with brown spots. Overall, this research successfully produced an effective and accurate classification system. The developed application has high practical potential as an early diagnosis aid to improve plant health management and reduce the potential for crop loss.

Rancang Bangun Sistem Virtual Mouse Dengan Hand Gesture Recognition Menggunakan Convolutional Neural Network ken, jeffrey; Darmanto, Tony; Hendro, Hendro
INTEKSIS Vol 12 No 1: Mei 2025
Publisher : LPPM Universitas Widya Dharma Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66003/inteksis.v12i1.10538

Pengembangan teknologi interaksi manusia dan komputer terus berkembang, terutama dalam konteks pengenalan gestur tangan untuk aplikasi pengendalian perangkat. Salah satu aplikasi yang menarik adalah perancangan sebuah sistem mouse virtual berbasis pengenalan gestur tangan menggunakan Convolutional Neural Network (CNN). Penelitian ini dilakukan untuk mengatasi keterbatasan perangkat input konvensional dan memanfaatkan teknologi modern untuk menciptakan sistem kontrol yang lebih canggih dan adaptif. Penelitian ini fokus pada pengembangan sistem yang mampu mengidentifikasi dan menginterpretasikan gestur tangan secara akurat dalam lingkungan real-time. Sistem yang diusulkan memanfaatkan kamera RGB untuk menangkap citra gestur tangan pengguna, yang kemudian diproses oleh CNN yang telah dilatih sebelumnya untuk mengenali gestur yang berbeda. Eksperimen dilakukan dengan menggunakan dataset gestur yang mencakup variasi pose dan orientasi tangan untuk mengevaluasi kinerja sistem dalam mengenali gestur dengan tingkat akurasi yang memadai. Hasil penelitian menunjukkan bahwa sistem dapat berhasil mengontrol pergerakan kursor pada layar komputer dengan akurasi yang tinggi, memvalidasi potensi aplikasi praktis dari teknologi ini dalam meningkatkan pengalaman pengguna dalam interaksi komputer. Implikasi dari penelitian ini adalah kontribusi terhadap pengembangan antarmuka pengguna yang lebih intuitif dan efektif melalui integrasi teknologi gestur tangan dalam aplikasi mouse virtual.

Rancang Bangun Sistem Informasi Administrasi Pada Dadung Gym Hendra Wijaya; Tony Darmanto; Sandi Tendean
INTEKSIS Vol 12 No 2 (2025): November 2025
Publisher : LPPM Universitas Widya Dharma Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66003/inteksis.v12i2.10589

The rapid development of fitness centers has prompted the need for efficient administrative systems. Dadung Gym in Pontianak faces challenges in managing member data and transactions due to reliance on traditional administrative methods. This study aims to design a mobile-based information system to reduce data processing errors, enhance service quality, and support strategic decision-making. Using an object-oriented approach with UML modeling, the system is developed with Flutter for the application framework, Firebaseas the database, and Visual Studio Code as the development tool. The new system automates data recording and offers features such as membership management, GPS-based attendance, and integrated reporting. Implementation of this mobile-based system is expected to improve service quality, simplify administrative processes, and provide a foundation for future business development at Dadung Gym Pontianak.

Rancang Bangun Sistem Virtual Mouse Dengan Hand Gesture Recognition Menggunakan Convolutional Neural Network Jeffrey Ken; Tony Darmanto; Hendro
INTEKSIS Vol 12 No 2 (2025): November 2025
Publisher : LPPM Universitas Widya Dharma Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66003/inteksis.v12i2.10591

The development of human-computer interaction technology continues to grow, especially in the context of hand gesture recognition for device control applications. One interesting application is designing a virtual mouse system based on hand gesture recognition using a Convolutional Neural Network (CNN). This research was conducted to overcome the limitations of conventional input devices and utilize modern technology to create a more sophisticated and adaptive control system. This research focuses on developing a system that is able to identify and interpret hand gestures accurately in a real-time environment. The proposed system utilizes an RGB camera to capture images of the user's hand gestures, which are then processed by a CNN that has been pre-trained to recognize different gestures. Experiments were carried out using a gesture dataset that included variations in pose and hand orientation to evaluate the system's performance in recognizing gestures with a sufficient level of accuracy. The research results show that the system can successfully control the movement of the cursor on the computer screen with high accuracy, validating the potential practical application of this technology in improving the user experience in computer interactions. The implication of this research is a contribution to the development of more intuitive and effective user interfaces through the integration of hand gesture technology in virtual mouse applications.

Aplikasi Klasifikasi Penyakit Pada Tanaman Jambu Air Menggunakan Metode CNN Antonius Oktavian Jethro; Tony Darmanto; Riyadi J. Iskandar
INTEKSIS Vol 12 No 2 (2025): November 2025
Publisher : LPPM Universitas Widya Dharma Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66003/inteksis.v12i2.10592

Diseases in water apple plants can significantly reduce the quality and quantity of the harvest, thus an accurate early classification system is needed. This research aims to develop an automatic classification system to assist in the early diagnosis of diseases in water apple plants. This system uses a Convolutional Neural Network (CNN) model with the MobileNetV2 architecture optimized through fine-tuning techniques. The dataset was obtained from Kaggle, Roboflow, and direct data collection, with a distribution of 80 percent training data, 10 percent validation data, and 10 percent testing data. The model was trained to recognize nine different conditions from images of leaves and fruits, then integrated into a web application. Testing results showed very good performance, with a final accuracy of 94 percent and a balanced F1-Score of 93 percent on unseen test data. However, the model faces challenges in distinguishing diseases with high visual similarity, especially in the class of leaves with brown spots. Overall, this research successfully produced an effective and accurate classification system. The developed application has high practical potential as an early diagnosis aid to improve plant health management and reduce the potential for crop loss.

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